1 / 24

Wrap-up and Review

Wrap-up and Review. PSY440 July 8, 2008. Repeated Measures & Mixed Factorial ANOVA. Basics of repeated measures factorial ANOVA Using SPSS Basics of mixed factorial ANOVA Using SPSS Similar to the between groups factorial ANOVA Main effects and interactions

mphyllis
Download Presentation

Wrap-up and Review

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Wrap-up and Review PSY440 July 8, 2008

  2. Repeated Measures & Mixed Factorial ANOVA • Basics of repeated measures factorial ANOVA • Using SPSS • Basics of mixed factorial ANOVA • Using SPSS • Similar to the between groups factorial ANOVA • Main effects and interactions • Multiple sources for the error terms (different denominators for each main effect)

  3. Example • Suppose that you are interested in how sleep deprivation impacts performance. You test 5 people on two tasks (motor and math) over the course of time without sleep (24 hrs, 36 hrs, and 48 hrs). Dependent variable is number of errors in the tasks. • Both factors are manipulated as within subject variables • Need to conduct a within groups factorial ANOVA

  4. Example

  5. Example

  6. Example • It has been suggested that pupil size increases during emotional arousal. A researcher presents people with different types of stimuli (designed to elicit different emotions). The researcher examines whether similar effects are demonstrated by men and women. • Type of stimuli was manipulated within subjects • Sex is a between subjects variable • Need to conduct a mixed factorial ANOVA

  7. Example

  8. Example

  9. General Specialized The Relationship Among Major Statistical Methods • The general linear model Multiple regression/correlation Bivariate correlation ANOVA t-test

  10. General Specialized The Relationship Among Major Statistical Methods • The general linear model Multiple regression/correlation Bivariate correlation ANOVA t-test

  11. The General Linear Model • Bivariate regression & Bivariate correlation • Special case of multiple regression • Multiple correlation (R) • Proportionate reduction in error (R2)

  12. General Specialized The Relationship Among Major Statistical Methods • The general linear model Multiple regression/correlation Bivariate correlation ANOVA t-test

  13. The t Test as a Special Case of ANOVA • t test • Two groups • ANOVA (F ratio) • More than two groups • Parallels in their basic logic • Numeric relationship of the procedures

  14. Links Between t Test for Independent Means & ANOVA

  15. General Specialized The Relationship Among Major Statistical Methods • The general linear model Multiple regression/correlation Bivariate correlation ANOVA t-test

  16. corresponds to the main effect X has two values Exp & Control Exp. Control ANOVA as a Special Case of the Significance Test of Multiple Regression ANOVACorrelation/Regression SSWithin = SSError SSTotal = SSTotal SSBetween = SSTotal – SSError R2 = r2 • ANOVA for two groups as a special case of the significance of a bivariate correlation

  17. Nominal coding ANOVA as a Special Case of the Significance Test of Multiple Regression • ANOVA for more than two groups as a special case of the significance of a multiple correlation

  18. ANOVA as a Special Case of the Significance Test of Multiple Regression • Factorial ANOVA: • Each main effect will have have a  associated with it. • Each interaction term will also have a  associated with it. • ANOVA for more than two groups as a special case of the significance of a multiple correlation

  19. General Specialized The Relationship Among Major Statistical Methods • The general linear model Multiple regression/correlation Bivariate correlation ANOVA t-test

  20. The t Test as a Special Case of the Significance Test for the Correlation Coefficient • Correlation coefficient • Degree of association between two variables • t test • Significance of the difference between the two population means • Both use the t distribution to determine significance • Recall: test statistic to test significance of Pearson’s r

  21. Relation Between Correlation and t Test for Independent Means

  22. Multiple regression/correlation General Bivariate correlation ANOVA Specialized t-test Choice of Statistical Tests • t test, ANOVA, and correlation can all be done as multiple regression • However, each usually used in specific research contexts • Correlation and regression automatically give estimates of effect size and not just significance

  23. Final Exam • Topics • Basic Probability • Descriptive statistics • Means • Standard deviation • Normal Distribution • Distribution of sample means (Central Limit Theorem) • Error types • Type 1 () • Type 2 () • Statistical power • Hypothesis testing • 1-sample z test • T-tests • 1-sample • Related samples • Independent samples • ANOVA • 1 factor • Repeated Measures • Factorial • Correlation & regression • Experimental Design

  24. Final Exam Make sure you know which test to use to answer different questions about a data set: One or two categorical variables? Two or more continuous variables? One or more categorical variable and one continuous variable? Also, refer to flow chart from lecture. When to use repeated measures vs. between groups ANOVA? When to use one, two, or paired samples t-tests?

More Related